Understanding the effects of contaminants that can diffuse into low‐permeability (“low‐k”) zones is crucial for effective groundwater remedial decision‐making. Because low‐k zones can serve as low‐level sources of contamination to more transmissive zones over time, an accurate evaluation of the impacts of matrix diffusion at contaminated sites is vital. This study compared numerical groundwater flow and transport simulations using MODFLOW/RT3D at a hypothetical site using three cases, each with increasing discretization of the vertical 10‐m thick domain: (1) a coarse multilayer heterogeneous grid based on one layer for each of four different hydrogeological units, (2) a “low‐resolution” discretization approach where the low‐k units were divided into several sublayers giving the model 10 layers, and (3) a “high‐resolution” numerical model with 199 layers that are a few centimeters thick. When comparing the results of each case, significant differences were observed between the discretizations used, even though all other model input data were identical. The conventional grid models (Cases 1 and 2) appeared to underestimate groundwater plume concentrations by a factor ranging from 1.1 to 36 when compared to the high‐resolution grid model (Case 3), and underestimated predicted cleanup times by more than a factor of 10 for some of the hypothetical sampling points in the modeling domain. These results validate the implication of Chapman et al. (2012), that conventional vertical discretization of numerical groundwater flow and transport models at contaminated sites (with layers that are greater than 1 m thick) can lead to significant errors when compared to more accurate high‐resolution vertical discretization schemes (layers that are centimeters thick).

中文翻译：

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垂直离散化对污染地下水基质扩散数值模拟的影响

了解可能扩散到低渗透率（“ low k ”）区域的污染物的影响对于有效的地下水补救决策至关重要。由于随着时间的流逝，低k区域可作为低污染源，而成为更多透射区域，因此准确评估基质在受污染地点扩散的影响至关重要。这项研究比较了在三种情况下使用MODFLOW / RT3D在一个假设地点进行的数值地下水流和输运模拟，每种情况下垂直10-m厚区域的离散化程度有所提高：（1）粗多层多层网格基于四层中的每一层不同的水文地质单位，（2）“低分辨率”离散化方法，其中低k单位分为几个子层，为模型提供10层，以及（3）199层（几厘米厚）的“高分辨率”数值模型。当比较每种情况的结果时，即使所有其他模型输入数据相同，在使用的离散化之间也观察到显着差异。与高分辨率网格模型（案例3）相比，常规网格模型（案例1和2）似乎低估了地下水羽流的浓度，范围为1.1到36，而预测的净化时间则低估了10倍以上。建模领域中一些假设的采样点。这些结果验证了Chapman等人的暗示。（2012），